Annals of family medicine
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Annals of family medicine · Nov 2022
Competencies for the Use of Artificial Intelligence in Primary Care.
The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintuple Aim (better patient outcomes, population health, and health equity at lower costs while preserving clinician well-being), inattention to primary care training in the use of AI-based tools risks the opposite effects, imposing harm and exacerbating inequalities. ⋯ Integrating these competencies will not be straightforward because of the breadth of knowledge already incorporated into family medicine training and the constantly changing technological landscape. Nonetheless, even incremental increases in AI-relevant training may be beneficial, and the sooner these challenges are tackled, the sooner the primary care workforce and those served by it will begin to reap the benefits.
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Annals of family medicine · Nov 2022
External Validation of the COVID-NoLab and COVID-SimpleLab Prognostic Tools.
Our objective was to externally validate 2 simple risk scores for mortality among a mostly inpatient population with COVID-19 in Canada (588 patients for COVID-NoLab and 479 patients for COVID-SimpleLab). The mortality rates in the low-, moderate-, and high-risk groups for COVID-NoLab were 1.1%, 9.6%, and 21.2%, respectively. ⋯ The 2 simple risk scores, now successfully externally validated, offer clinicians a reliable way to quickly identify low-risk inpatients who could potentially be managed as outpatients in the event of a bed shortage. Both are available online (https://ebell-projects.shinyapps.io/covid_nolab/ and https://ebell-projects.shinyapps.io/COVID-SimpleLab/).
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Annals of family medicine · Nov 2022
Linking a Survey of Clinician Benzodiazepine-Related Beliefs to Risk of Benzodiazepine Prescription Fills Among Patients in Medicare.
In this pilot study, we used a Medicare sample to identify primary care clinicians who prescribed a benzodiazepine (BZD) in 2017 and surveyed a random sample (n = 100) about BZD prescribing. Among 61 respondents, 11.5% (SD 5.9) of their patient panels filled a BZD prescription. ⋯ We highlight the potential of using Medicare claims to sample clinicians. Using claims-based objective measures presents a new method to inform the development of behavior-change interventions.